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Related Articles from SNS
Multi-resolution Enhancement for Full Spectrum Neural Representations
arXiv:2509.15494v2 Announce Type: replace-cross Abstract: Scientific data acquisition continues to outpace storage and analysis capabilities, making voxel-based representations increasingly intractable. Implicit neural representations (INRs) offer a promising solution by encoding signals through coordinate-based neural networks, serving as surrogates of data, with computational and storage requirements scaling with network complexity rather than data dimensionality. However, smaller INRs...
Multi-resolution Enhancement for Full Spectrum Neural Representations
arXiv:2509.15494v2 Announce Type: replace Abstract: Scientific data acquisition continues to outpace storage and analysis capabilities, making voxel-based representations increasingly intractable. Implicit neural representations (INRs) offer a promising solution by encoding signals through coordinate-based neural networks, serving as surrogates of data, with computational and storage requirements scaling with network complexity rather than data dimensionality. However, smaller INRs struggle...
MoE-dqINR: A Unified Mixture-of-Experts Implicit Neural Representation Framework for Scan-Specific Dynamic and Quantitative MRI Reconstruction
arXiv:2605.31302v1 Announce Type: cross Abstract: Undersampled magnetic resonance imaging (MRI) reconstruction seeks to recover temporally or contrast-varying image series from incomplete multicoil k-space data while preserving state-dependent fidelity for dynamic and quantitative MRI (qMRI). Existing scan-specific implicit neural representations (INRs) often use monolithic spatiotemporal coordinate fields, explicit subspaces, motion or deformation models, calibration variables, or...
JA-SIREN: Deterministic Initialization for Sinusoidal Networks via Spectral Matching
Announce Type: new Abstract: Existing implicit neural representation (INR) approaches suffer from stochastic initialization that does not guarantee consistent or high-quality performance across runs, with variations reaching more than 2.5 dB (78%) in image regression. This variation is problematic for scientific computing and simulation, where result reproducibility is crucial. To address this problem, we present Jacobi-Anger Sinusoidal Representation Network (JA-SIREN), a deterministic...
Optimizing Rank for High-Fidelity Implicit Neural Representations
arXiv:2512.14366v2 Announce Type: replace Abstract: Implicit Neural Representations (INRs) based on vanilla Multi-Layer Perceptrons (MLPs) are widely believed to be incapable of representing high-frequency content. This has directed research efforts towards architectural interventions, such as coordinate embeddings or specialized activation functions, to represent high-frequency signals. In this paper, we challenge the notion that the low-frequency bias of vanilla MLPs is an intrinsic,...
Architecture Shapes Transfer Specificity in Implicit Neural Representations
arXiv:2606.06827v1 Announce Type: new Abstract: Transfer in coordinate networks is often measured by warm-start gain, but whether that gain reflects source-specific structure or generic weight reuse is less clear. We study this question across three implicit neural representation (INR) families, SIREN, ReLU MLPs, and Fourier-feature MLPs, using controlled analytic tests, a 2D lid-driven-cavity Navier--Stokes benchmark, and 1D PDE reference-solution suites for heat, viscous Burgers, and...
ParCo-SDF: Learning Prior-Free Partial-to-Complete Signed Distance Fields of Deformable Objects
arXiv:2605.29417v2 Announce Type: replace Abstract: This study addresses the partial-to-complete geometry reconstruction of deformable objects (DOs) from point-cloud observations toward precise DO manipulation. Recent DO reconstruction approaches often adopt implicit neural representations (INRs) to model continuous surfaces as well as capture structural variability. However, these methods typically rely on object-specific shape priors that improve training stability and limit generalization.
Ahmedabad rental market: A look at affordability, connectivity and smart city benefits
Rapid urbanization, rising educational and job opportunities has fueled the demand for rental housing. With an increase of 2% in rental values, Mumbai remains the most expensive rental market, as shown in MagicBricks Rental Index report for Q4 of FY2026. However, Ahmedabad along with others like Noida and Greater Noida have appeared in the list of the most affordable cities for tenants.
Rupee begins week at 95.35 against US dollar amid Middle East chaos
Rupee began the week on a negative note, with market sentiment weighed down by a stronger dollar, rising crude oil prices and escalating geopolitical tensions. On Monday, the domestic currency opened at 95.35 against the US dollar in the interbank foreign exchange market, slipping 17 paise from its previous close of 95.18. The decline comes after rupee posted its strongest single-day gain in nearly two months on Friday, when it appreciated 56 paise following the Reserve Bank's measures aimed...
Explained: How Nihal Sarin secured India's first-ever Esports Nations Cup chess invite
NEW DELHI: It has been a week of double delight for Indian Grandmaster Nihal Sarin. First, his qualification for the Esports Chess World Cup became official. Shortly after, the 21-year-old became the first Indian to secure a direct qualification invite for the main event of the inaugural edition of Esports Nations Cup (ENC) 2026.